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510 results for “storms”

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zenodo40/100

Glider, turbulence and ADCP datasets used in the manuscript "Storm-induced turbulence alters shelf sea vertical fluxes"

Measurements of shear microstructure, temperature, conductivity, and fluorescence of chlorophyll-a of a stratified water column were taken in the German Bight of the North Sea in Summer 2014. During the measurement period, a storm entered the study region and mixed the water column thoroughly, modifying water column dynamics. The measured quantities were used to estimate turbulence, stratification, mixing, water column stability and changes in the signal of chlorophyll-a.

opencc-by-4.0May 2019View details →

zenodo40/100

Paired time series of daily discharge and storm surge

This dataset presents daily time series of discharge and maximum storm surge at river mouths globally from 1980 - 2014.   Daily river discharge is the product of routing the mean daily runoff of the JULES model from the eartH2Observe WRR2 reanalysis data at 0.5° resolution (Best et al., 2011; Clark et al., 2011; Schellekens et al., 2017) with CaMa-Flood at a 0.25° resolution (Yamazaki et al., 2011). The maximum daily storm surge is obtained from the Global Tide and Surge Model (GTSM) (Muis et al., 2016; Verlaan et al., 2015). Each discharge location at the river mouth of coastal catchments larger than 1,000 km2 is paired with the nearest (≤ 75 km) GTSM output location (Eilander et al., 2019).

opencc-by-4.0Jun 2019View details →

zenodo40/100

The Impact of the 8-10 March 2012 Geomagnetic Storm on Inner Zone Protons as Measured by Van Allen Probes

Dataset for manuscript ctr.mat: test-particle count, Fig4 psdgoes.mat, psdob0.mat: PSD from RD, Fig5, 6, 8 mar2012-ts05-flux-777001.txt, mar2012-ts05-flux-777003.txt: test-particle trajectories, Fig7

opencc-by-4.0Aug 2024View details →

zenodo40/100

Data for publication "The Thermosphere was Poorly Predictable not Only During but also Before and After the Starlink Storm on 3-4 February 2022"

This dataset are used to plot figures in the article "The Thermosphere was Poorly Predictable not Only During but also Before and After the Starlink Storm on February 3-4, 2022". Data files in CSV (comma-separated values) format contain modeling and observational values. Modeling values obtained from the Field Line Interhemispheric Plasma (FLIP) model and Arctic MERRA-2 Wind model. Observational values consist the ionosonde measurments, planetary geomagnetic (Kp) and solar activity indices (F10.7), variations of the solar wind parameters. Data files contain data for the period from February 1 to 9, 2022 and from December 21 to 23, 2021.

opencc-by-4.0Sep 2024View details →

zenodo40/100

Data sets for distributed ionospheric L-band scintillation and TEC observations made in the American sector during the March 23-24, 2023 geomagnetic storm

These data sets contain the scintillation measurements presented in the manuscript titled, "On the extraordinary L-band scintillation event observed in the American sector during the March 23-24, 2023 geomagnetic storm". The HDF5 files are organized by constellations and satellites. Each satellite includes the following parameters: Azimuth (AZIM), Elevation (ELEV), Number of Samples (NOS), Amplitude Scintillation Index (S4), 1-minute average SNR (SNR), relative Total Electron Content (PTEC), and Time of Week in seconds (S_TW)

opencc-by-4.0Oct 2024View details →

zenodo40/100

Datasets from "Auroral Energy Deposition and Conductance During the 2013 St. Patrick's Day Storm: Meso-Scale Contributions" by Gabrielse et al.

1. README File for netCDF Data to be published alongside “Mesoscale Contributions to Auroral Energy Deposition and Conductance During the 2013 St. Patrick’s Day Storm” by Christine Gabrielse et al. in the Journal of Geophysical Research. The data to be stored on Zenodo (<a href="https://zenodo.org/">https://zenodo.org/</a>) are in a netCDF format. This README applies to the following files:    thg_ej_all-sky-imager_20130317050000_v01.nc    thg_ej_all-sky-imager_20130317060000_v01.nc    thg_ej_all-sky-imager_20130317070000_v01.nc    thg_ej_all-sky-imager_20130317080000_v01.nc    thg_ej_all-sky-imager_20130317090000_v01.nc    thg_ej_all-sky-imager_20130317100000_v01.nc    thg_ej_all-sky-imager_20130317110000_v01.nc    thg_ej_all-sky-imager_20130317120000_v01.nc    thg_ej_all-sky-imager_20130317130000_v01.nc   The following are attributes published within the netCDF’s metadata: SUMMARY: FILENAME:    thg_ej_all-sky-imager_20130317050000_v01.nc   PROJECT:    STP>Solar-Terrestrial Physics   SOURCE_NAME:    THG>THEMIS (Time History of Events and Macroscale Interactions during    Substorms) Ground-Based   DISCIPLINE:    Space Physics>Ionospheric Science    Space Physics>Magnetospheric Science   DATA_TYPE:    EJ>Earth Camera Images, processed   DESCRIPTOR:    All-Sky-Imager   FILE_NAMING_CONVENTION:    source_datatype_descriptor_yyyyMMddHHmmss   DATA_VERSION:    01   PI_NAME:    Christine Gabrielse   PI_AFFILIATION:    The Aerospace Corporation   TEXT:    Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS    white light all-sky-imagers. See Gabrielse et al. (2021, Frontiers) and    Gabrielse et al. (2024, JGR) for derivation methodology.   INSTRUMENT_TYPE:    Ground-Based Imagers   MISSION_GROUP:    Ground-Based Investigations   LOGICAL_SOURCE:    thg_ej_all-sky-imager   LOGICAL_FILE_ID:    thg_ej_all-sky-imager_00000000000000_v01   LOGICAL_SOURCE_DESCRIPTION:    Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS    white light all-sky-imagers.   TIME_RESOLUTION:    3s   RULES_OF_USE:    Invitation to co-authorship for use of this data is required. It is best to    reach out to Dr. Gabrielse early in the project for guidance.   GENERATED_BY:    Christine Gabrielse   ACKNOWLEDGEMENT:    The work effort for this project was gratefully funded by NASA grants    80NSSC20K0725, 80GSFC22CA011, NAS5-02099, 80NSSC21K1552, AFOSR Grant    FA9559-16-1-0364   GLOBAL ATTRIBUTES: PROJECT:    STP>Solar-Terrestrial Physics SOURCE_NAME:    THG>THEMIS (Time History of Events and Macroscale Interactions during    Substorms) Ground-Based DISCIPLINE:    Space Physics>Ionospheric Science    Space Physics>Magnetospheric Science DATA_TYPE:    EJ>Earth Camera Images, processed DESCRIPTOR:    All-Sky-Imager FILE_NAMING_CONVENTION:    source_datatype_descriptor_yyyyMMddHHmmss DATA_VERSION:    01 PI_NAME:    Christine Gabrielse PI_AFFILIATION:    The Aerospace Corporation TEXT:    Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS    white light all-sky-imagers. See Gabrielse et al. (2021, Frontiers) and    Gabrielse et al. (2024, JGR) for derivation methodology. INSTRUMENT_TYPE:    Ground-Based Imagers MISSION_GROUP:    Ground-Based Investigations LOGICAL_SOURCE:    thg_ej_all-sky-imager LOGICAL_FILE_ID:    thg_ej_all-sky-imager_00000000000000_v01 LOGICAL_SOURCE_DESCRIPTION:    Parameters (energy flux, mean energy, Hall conductance) derived from the THEMIS    white light all-sky-imagers. TIME_RESOLUTION:    3s RULES_OF_USE:    Invitation to co-authorship for use of this data is required. It is best to    reach out to Dr. Gabrielse early in the project for guidance. GENERATED_BY:    Christine Gabrielse ACKNOWLEDGEMENT:    The work effort for this project was gratefully funded by NASA grants    80NSSC20K0725, 80GSFC22CA011, NAS5-02099, 80NSSC21K1552, AFOSR Grant    FA9559-16-1-0364   DIMENSIONS: EPOCH:    1200 LATITUDE:    400 LONGITUDE:    400   VARIABLES: EPOCH: CAT_DESC:    Time in seconds since 1970-01-01 00:00:00 TIME_SCALE:    UTC TIME_BASE:    1970 (POSIX) FIELDNAM:    Time in seconds since 1970-01-01 00:00:00 FILLVAL:    LONG = -2147483648 FORMAT:    I10 UNITS:    S VALIDMIN:    LONG = 1363496400 VALIDMAX:    LONG = 1363528800 VAR_TYPE:    support_data LATITUDE: _FILLVALUE:    FLOAT = NaN CAT_DESC:    Geodetic latitude FIELDNAM:    Latitude FORMAT:    F4.1 FILLVAL:    DOUBLE = -1.0000000e+31 UNITS:    deg VALIDMIN:    DOUBLE = 45.000000 VALIDMAX:    DOUBLE = 84.900000 VAR_TYPE:    support_data LONGITUDE: _FILLVALUE:    FLOAT = NaN CAT_DESC:    Geodetic longitude FIELDNAM:    Longitude FORMAT:    F5.1 FILLVAL:    DOUBLE = -1.0000000e+31 UNITS:    Deg VALIDMIN:    DOUBLE = 180.00000 VALIDMAX:    DOUBLE = 339.60000 VAR_TYPE:    support_data CONDUCTANCE: _FILLVALUE:    DOUBLE = NaN CAT_DESC:    Hall conductance in a 2D grid organized by geographic latitude and longitude,    units of mho DEPEND_0:    Epoch DEPEND_1:    Latitude DEPEND_2:    Longitude DISPLAY_TYPE`:    Image FIELDNAM:    Hall conductance FILLVAL:    DOUBLE = -1.0000000e+31 FORMAT:    F8.6 LABLAXIS:    Hall conductance UNITS:    Mho VALIDMIN:    DOUBLE = 0.00043800000 VALIDMAX:    DOUBLE = 88.000000 VAR_TYPE:    Data Energy flux: _FILLVALUE:    FLOAT = NaN CAT_DESC:    Precipitated energy flux in a 2D grid organized by geographic latitude and    longitude, units of ergs/cm^2/s DEPEND_0:    Epoch DEPEND_1:    Latitude DEPEND_2:    Longitude DISPLAY_TYPE`:    Image FIELDNAM:    Energy Flux (ergs/cm^2/s) FILLVAL:    DOUBLE = -1.0000000e+31 FORMAT:    F9.4 LABLAXIS:    energy flux UNITS:    ergs/cm^2/s VALIDMIN:    DOUBLE = 0.010000000 VALIDMAX:    DOUBLE = 1100.0000 VAR_TYPE:    Data ENERGY: _FILLVALUE:    FLOAT = NaN CAT_DESC:    Mean energy of the precipitated population in a 2D grid organized by geographic    latitude and longitude, units of keV DEPEND_0:    Epoch DEPEND_1:    Latitude DEPEND_2:    Longitude DISPLAY_TYPE`:    Image FIELDNAM:    Energy (keV) FILLVAL:    DOUBLE = -1.0000000e+31 FORMAT:    F6.3 LABLAXIS:    Energy UNITS:    keV VALIDMIN:    DOUBLE = 0.010000000 VALIDMAX:    DOUBLE = 22.000000 VAR_TYPE:    Data   Examples of the data are as follows: EPOCH: data.epoch.data[0] =   1363496400   This data is presented as number of seconds since January 1, 1970 in UT. The example above converts to 2013-03-17/05:00 UT. There are 1200 time values stored in each file.   LATITUDE: data.latitude.data[0] = 45.0000   This data is the geographic latitude in degrees of the 400x400 grid of data points. There are 400 latitude values stored in each file.   LONGITUDE: data.LONGITUDE.data[0] =  180.000   This data is the geographic longitude in degrees of the 400x400 grid of data points. There are 400 longitude values stored in each file.   CONDUCTANCE: data.conductance.data[0] = -1.0000000e+31   This data is the Hall conductance in mho measured at 45 deg latitude, 180 deg longitude. The value in this example indicates that no conductance was measured here. A valid value would be something in the range of 0.00043800000 to 88 mho. There are 1200x400x400 conductance values stored in each file.   ENERGY FLUX: data.eflux.data[0] = -1.00000e+31   This data is the energy flux in ergs/cm^2/s measured at 45 deg latitude, 180 deg longitude. The value in this example indicates that no energy flux was measured here. A valid value would be something in the range of 0.01 to 1100.0000 ergs/cm^2/s. There are 1200x400x400 energy flux values stored in each file.   ENERGY: data.energy.data[0] = -1.00000e+31   This data is the energy in keV measured at 45 deg latitude, 180 deg longitude. The value in this example indicates that no energy was measured here. A valid value would be something in the range of 0.01 to 22 keV. There are 1200x400x400 energy values stored in each file.   2. README for text file Data to be published alongside “Mesoscale Contributions to Auroral Energy Deposition and Conductance During the 2013 St. Patrick’s Day Storm” by Christine Gabrielse et al. in the Journal of Geophysical Research. This README applies to the following files:    march172013_fortyukon_photometer_products.dat    march172013_pokerflat_photometer_products.dat Header information in the files describe the contents.  These are the photometer derived data taken on March 17, 2023. They include the time [UT], energy flux (Q) [ergs/cm^2/s], average energy (Eavg) [keV], and oxygen scale factor (fo).

opencc-by-4.0Oct 2024View details →

zenodo40/100

Distribution and occurrence frequency of dB/dt spikes during magnetic storms 1980 - 2019

Dataset and files linked to the study  "Distribution and occurrence frequency of dB/dt spikes during magnetic storms 1980 - 2019" by A. Schillings et al.,  in Space Weather.

opencc-by-4.0Jun 2021View details →

zenodo40/100

Sharpening of Cold Season Storms over the Western US: companion dataset

This folder includes the intermediate data and scripts (of plots in the main text) for the following manuscript: Chen et al., Sharpening of Cold Season Storms over the Western US. The simulations are done using WRF V3.8 at PNNL. A historical simulation ("NARR") is done for 1981-2010, and five future simulations ("CanESM2", "CESM1-CAM5", "GFDL-ESM2M", "HadGEM2-ES", "MPI-ESM-MR") are done for 2041-2070 using the Pseudo Global Warming (PGW) approach. For the WRF model configuration and the simulation details, please refer to the abovementioned manuscript and Chen et al. (2018). The precipitation objects are then identified using the 5 mm/day threshold. The paths in the scripts are self-consistent. You can just download the .zip file and run the Jupyter notebook to reproduce the figures in the paper.   Reference: Chen, X., L. R. Ruby, Y. Gao, Y. Liu, M. Wigmosta, and M. Richmond (2018), Predictability of Extreme Precipitation in Western U.S. Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration, Geophys. Res. Lett. doi: <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2018GL079831">10.1029/2018GL079831</a> Chen, X., L. R. Ruby, Y. Gao, Y. Liu, and M. Wigmosta (2023), Sharpening of cold-season storms over the western United States, Nat. Clim. Change. doi: <a href="https://www.nature.com/articles/s41558-022-01578-0">10.1038/s41558-022-01578-0</a>

opencc-by-4.0Dec 2022View details →

zenodo40/100

Dataset for "Three-dimensional modeling of the ground electric field in Fennoscandia during the Halloween geomagnetic storm", Marshalko et al. (2023), Space Weather

Results of 3-D modeling of the ground electric field in Fennoscandia during the Halloween geomagnetic storm in 2003 (29-31 October). Electric_field_YYYYMMDDHHMMSS_YYYYMMDDHHMMSS.h5 files (in hdf5 format) contain horizontal electric field components Ex and Ey (in mV/km) corresponding to 6 h of data and latitude and longitude grids corresponding to Ex and Ey arrays. Ex and Ey are 2160x567x543 arrays (temporal resolution is 10 s, thus, 2160 time steps). Latitude and Longitude are 567x543 arrays. All values are in single-precision floating-point format. Electric field values were obtained with the use of the conductivity-based inducing source following Marshalko et al. (2023). Files Electric_field_CB_20031029000000_20031031235950.dat, Electric_field_MT_20031029000000_20031031235950.dat, and Electric_field_SECS_20031029000000_20031031235950.dat contain the ground electric field time series (in mV/km) modeled during the Halloween geomagnetic storm in 2003 (29-31 October) at IMAGE magnetometers' locations, Mäntsälä Finnish natural gas pipeline GIC recording point (MAN), and Point X located 0.5 degrees north of MAN. The files are in plain-text (column-based) format. Electric field values in Electric_field_CB_20031029000000_20031031235950.dat, Electric_field_MT_20031029000000_20031031235950.dat, and Electric_field_SECS_20031029000000_20031031235950.dat were obtained with the use of the conductivity-based inducing source, MT intersite impedance method, and Spherical Elementary Current Systems (SECS) based approach, correspondingly, following Marshalko et al. (2023).

opencc-by-4.0Dec 2022View details →

zenodo40/100

Dataset of Last Interglacial climate from publication "Modeled storm surge changes in a warmer world: the Last Interglacial" by P. Scussolini et al.

Results from the simulation of Last Interglacial (Eemian) climate with climate model CESM1.2. Variables are: sea-level pressure (PSL); meridional wind (V), and zonal wind (U). Time step is 6-hourly. Detailed description of the methods are in the original publication: Scussolini, P., Dullaart, J., Muis, S., Rovere, A., Bakker, P., Coumou, D., Renssen, H., Ward, P. J., and Aerts, J. C. J. H.: Modelled storm surge changes in a warmer world: the Last Interglacial, EGUsphere, 2022, 1-20, 10.5194/egusphere-2022-101, 2022.

opencc-by-4.0Dec 2022View details →

zenodo40/100

Dataset of pre-industrial climate from publication "Modeled storm surge changes in a warmer world: the Last Interglacial" by P. Scussolini et al.

Results from the simulation of pre-industrial climate with climate model CESM1.2. Variables are: sea-level pressure (PSL); meridional wind (V), and zonal wind (U). Time step is 6-hourly. Detailed description of the methods are in the original publication: Scussolini, P., Dullaart, J., Muis, S., Rovere, A., Bakker, P., Coumou, D., Renssen, H., Ward, P. J., and Aerts, J. C. J. H.: Modelled storm surge changes in a warmer world: the Last Interglacial, EGUsphere, 2022, 1-20, 10.5194/egusphere-2022-101, 2022.

opencc-by-4.0Dec 2022View details →

zenodo40/100

STORM Vectashield datasets (Tubulin)

Data generated at EPFL (LEB) under the supervision of Suliana Manley. Microscope: IX71 (Olympus) with 100x 1.3NA objective (Olympus, UplanFL) mounted on a piezo objective scanner (P-725 PIFOC, Physik Instrumente) +1.6x magnification lens (except Fig1 dataset, 160nm px) Laser:  641 nm (Coherent, CUBE 640–100C)  and 561 nm (Coherent Sapphire) (Fig7, Cy3) Intensity on the sample ≈ 1–2 kW/cm2 Filters: multiband dichroic (89100bs, Chroma) + bandpass emission filter (ET700/75, ET600/75 (Cy3) Chroma), Camera: IxonEM+ (Andor) with an effective 100 nm pixel size and using the conventional CCD amplifier (except when specified, check the  _readme.txt files in each dataset) See spec sheet ("Spec-Sheet_iXon.JPG") "FigX" datasets were used to generated the figures of the article "Simple Buffer for 3D STORM Microscopy" (<a href="https://doi.org/10.1364/BOE.4.000885">https://doi.org/10.1364/BOE.4.000885</a>): Fig1: STORM Imaging of Alexa647 in pure Vectashield (px 160nm) Fig4: STORM Imaging of Alexa647 in 25% and 50% Vectashield in Glycerol-TRIS Fig5: STORM Imaging of Alexa647 in 25% Vectashield - 75% TRIS-Glycerol  + 1% NPG / 20 mM DABCO /10 mM Lipoic Acid Fig6: 3D-STORM Imaging of Alexa647 in 20% Vectashield - 80% TRIS-Glycerol (astigmatism) Fig:7: STORM Imaging of Alexa647 in 25% Vectashield - 75% TDE and 50% Vectashield- 50% PBS Fig8: STORM Imaging of CEP152-Cy3 in 40% Vectashield + 1% NPG + 20 mM DABCO Fig9: STORM Imaging of CF647 and Cy5 in Vectashield HD datasets: 2D (& one 3D) high density datasets, one of which ("2DHD6") was used for the 2013 IEEE ISBI SMLM challenge, while another ('2DHD_3") was used in "FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data" (<a href="https://doi.org/10.1038/srep04577">https://doi.org/10.1038/srep04577</a>) "Vecta_20pc_1" was used to generate Fig S13 in "FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data" (<a href="https://doi.org/10.1038/srep04577">https://doi.org/10.1038/srep04577</a>) - similar conditions and samples as with High Density but with Low Density. "_STD' files correspond to the standard deviation of the raw datasets. "_STORM" files correspond to STORM reconstructions obtained with Detection of Molecules (DoM) plugin for ImageJ (<a href="https://github.com/UU-cellbiology/DoM_Utrecht">https://github.com/UU-cellbiology/DoM_Utrecht</a>)." Sample preparation: Cell Culture: COS-7 were cultured in DMEM 10% FBS and plated on Ethanol-cleaned 25 mm size 1 cover-glass (Menzell) or 25mm Hestzig cover-glass (with embedded gold colloids fiducials) Fixation: Cells were pre-extracted for 10s in 0.5% Triton X-100 (Triton) in BRB80 (80 mM PIPES, 1 mM MgCl2, 1 mM EGTA, adjusted to pH 6.8 with KOH) supplemented with 4 mM EGTA, washed in PBS, fixed for 10 min in − 20°C-Methanol and washed again in PBS. Immunostaining (all done at room temperature): Blocking 30 min in 5% BSA, then incubation 1.5h with 1:1000 primary antibody in PBS - 1% BSA - 0.2% Triton (PBST), 3 washes with PBS-0.2% Triton, then incubation  45min in PBST with 1:1000 secondary antibody and 3 washes with PBS-0.2% Triton. Primary antibody (except when specified in readme.txt file): mouse anti alpha-tubulin (Sigma-Aldrich, T5168) Secondary antibody (except when specified in readme.txt file):  goat anti-mouse Alexa-647 F(ab)2 secondary antibody fragments (Life Technologies, A-21237).

opencc-by-4.0Feb 2023View details →

zenodo40/100

The SafeSpace magnetospheric models sample forecast for the 2015 St Patrick's geomagnetic storm

This dataset presents the sample forecast of the magnetosphere models in the SafeSpace project, for the March 2015 St Patrick's storm. It is build from a synthetic solar wind forecast at L1 and corresponding Kp forecast. This forecast if fed in the SPM plasma density model, as well as in a VLF wave intensities model, yielding the dataset presented here. All files are in the CDF file format. <ul> <li>The <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/GEOIDX_20150301.cdf">GEOIDX_20150301.cdf</a> file contains the synthetic solar wind and Kp ensemble forecast.</li> <li>The <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/Bw2_20150301.cdf">Bw2_20150301.cdf</a> file contains the corresponding VLF wave intensities.</li> <li>The <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/SPM_dens_20150301.cdf">SPM_dens_20150301.cdf</a> file contains the corresponding plasma densities.</li> <li>The <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/SafeSpace_RBSP_A_Nowcast.cdf">SafeSpace_RBSP_A_Nowcast.cdf</a> and <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/SafeSpace_RBSP_A_Nowcast.cdf">SafeSpace_RBSP_B_Nowcast.cdf</a> files contains the reconstructed electron fluxes along the RBSP spacecrafts for the whole March 2015 month, using data assimilation in the SafeSpace pipeline.</li> <li>The <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/SafeSpace_RBSP_A_Nowcast.cdf">SafeSpace_RBSP_A_Forecast.cdf</a> and <a href="https://zenodo.org/api/files/eb6a5ea3-366a-4830-bb14-71799a6f00cf/SafeSpace_RBSP_A_Nowcast.cdf">SafeSpace_RBSP_B_Nowcast.cdf</a> files contains a 4 days forecast of the electron fluxes along the RBSP spacecrafts for March 17th to March 20th, 2015.</li> </ul> This dataset and the SafeSpace pipeline is described in details in the article by Brunet et al. "Improving the electron radiation belt nowcast and forecast using the SafeSpace data assimilation modelling pipeline", currently in review in AGU Space Weather.

opencc-by-4.0Mar 2023View details →

dryad40/100

Solar wind plasma, magnetic field parameters and geomagnetic storm index SYM-H from 2000 to 2020

SYM-H index is used to quantify the intensity of geomagnetic storm. Its temporal variation is related to the solar wind plasma and magnetic field parameters. This dataset offers time series of solar wind density, solar wind velocity and solar wind magnetic field, SYM-H index. The python and matlab code files for processing and plotting data are also included.

opencc-zeroApr 2023View details →

zenodo40/100

WACCMX STORM QUIET TIME EDENS AND EXB

This dataset is the WACCM-X model data for November 3 and 4 2021. It shows the electron density and E x B drift variation between 20:00 and 23:00 UT for both days.

opencc-by-4.0Apr 2023View details →

zenodo40/100

Data from Zeppenfeld et al. 2023: "Winter storm risk assessment in forests with high resolution gust speed data", Eur. J. For. Res.

Single-tree damage data from winter storm event "Lothar" 1999 in Baden-Wurttemberg, Germany. The data set includes the response (damage or no damage) and covariates for model parametrisation as described in Zeppenfeld et al. (2023).

opencc-by-4.0May 2023View details →

zenodo40/100

Attributing European forest disturbances to storm and fire

This repository contains maps attributing each disturbance patch of the <a href="https://zenodo.org/record/4570157#.YFB27i337OQ">European Forest Disturbance Map</a> (version 1.1.4) to bark beetle/wind, fire or other disturbances (mostly harvest). The dataset is based on methods described in following paper, but have been updated with new reference data covering now also bark beetle disturbances:  Senf, C. and Seidl, R. (2021) Storm and fire disturbance in Europe: Distribution and trends. Global Change Biology. <a href="https://doi.org/10.1111/gcb.15679">https://doi.org/10.1111/gcb.15679</a> To get the year of disturbance, please see the underlaying disturbance maps (version 1.1.4.; link given above). Map classes: NA = no disturbance 1 = bark beetle or wind disturbances (both classes had to be grouped due to technical reasons) 2 = fire disturbances 3 = other disturbances, mostly harvest but might include salvage logging go small-scale natural disturbances and infrequent other natural agents (e.g., defoliation, avalanches, etc.) Reference system: The spatial reference system is EPSG 3035 (ETRS89 / LAEA Europe). Word of caution: Remote sensing-based maps, while fascinating to look at, contain errors. If you intent to use the map for your research, please carefully read the discussion on limitations in the paper accompanying the dataset. There will be many instances where the attribution (or even disturbance detection) is wrong. The maps are intended to give a broad, continental-scale overview on the distribution of disturbance agents.

opencc-by-4.0Mar 2021View details →

zenodo40/100

Dataset for "Assessing Storm Surge Multi-Scenarios based on Ensemble Tropical Cyclone Forecasting" paper

1000 ensemble track forecast of tropical cyclone Hagibis (2019) is provided in NetCDF format and the computed storm surge forecast is provided in the Excel file.

opencc-by-4.0Aug 2023View details →

zenodo40/100

philip928lin/Flood-Risks-of-Cyber-physical-Attacks-in-a-Smart-Storm-Water-System: Flood Risks of Cyber-physical Attacks in a Smart Storm Water System

This is the code archive for the publication "Flood Risks of Cyber-physical Attacks in a Smart Storm Water System" in Water Resources Research.

opencc-by-4.0Oct 2023View details →

ClinicalTrials.gov40/100

Study to Assess the Efficacy and Safety of Ruxolitinib in Patients With COVID-19 Associated Cytokine Storm

ClinicalTrials.gov study NCT04362137. IPD Sharing: YES. Countries: 12. Publications: 1.

controlledIPD-YESFeb 2026View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record